| NSF Org: |
IIS Division of Information & Intelligent Systems |
| Recipient: |
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| Initial Amendment Date: | March 17, 2015 |
| Latest Amendment Date: | August 1, 2018 |
| Award Number: | 1464376 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
William Bainbridge
IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | September 1, 2015 |
| End Date: | August 31, 2019 (Estimated) |
| Total Intended Award Amount: | $174,987.00 |
| Total Awarded Amount to Date: | $190,987.00 |
| Funds Obligated to Date: |
FY 2016 = $88,591.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
2221 UNIVERSITY AVE SE STE 100 MINNEAPOLIS MN US 55414-3074 (612)624-5599 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
Keller Hall, 200 Union St., SE Minneapolis MN US 55455-0159 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
CRII CISE Research Initiation, HCC-Human-Centered Computing |
| Primary Program Source: |
01001617DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
This project contributes to our understanding of the relationship between people and technology by addressing two related core open problems in the field: enacting anonymity online and managing strong tie support in online communities. Issues of privacy, anonymity, equality of participation, engagement, and social support are of interest in many online contexts. This work extends the theory and practice of Social Computing and Human-Computer Interaction by contributing a rigorous empirical investigation of online anonymity and peer support practices in online communities for recovery from addiction and alcoholism. Additionally, this project will contribute to the design of new technologies to advance national health and welfare - addressing the "treatment gap" for addicts and alcoholics who seek recovery by leveraging novel technology to connect them with treatment and peer support.
These topics will be investigated through four specific research activities. First, participatory observation will be conducted of an online community for recovering addicts and alcoholics. Second, data will be downloaded from this online community over the course of a year to develop a quantitative understanding of the evolution of the relationships and activities in this community over time. Third, in-depth interviews with members of this community will examine the role of leadership in these online health communities and the factors that contribute to strong social support online. Finally, participatory design workshops with recovering addicts and alcoholics will integrate, vet, and validate the findings of these empirical investigations and develop novel ecologically-valid technology prototypes for supporting recovery from addiction and alcoholism.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Nobody should have to face a major health issue alone. Our work investigated how people turn to online communities to find social support while facing health conditions like substance use disorders or cancer. Based on our findings, we built novel computing technologies to help people get the support they need.
INTELLECTUAL MERIT:
To understand how people manage the tension between online self-disclosure and privacy, we carried out a series of studies which included in-depth interviews with more than 50 people with health conditions, online questionnaires with over 300 participants, and quantitative analysis of over 25,000 accounts in an online community for substance use disorders and over 85,000 accounts in an online community focusing on cancer. From this body of work, we found that people leverage a "social contract" interpretation of anonymity to manage privacy and access within these communities. We also found that online social support enhanced and supplemented in-person connection (rather than replacing it) and this support was critical for people's continued participation and benefit in online health communities. People facing major health conditions wanted technology to help amplify in-person connections and support networks to help them manage their conditions.
Based on these findings, we worked with collaboration with people facing health conditions to design novel technologies to address challenges they viewed as critical to their recovery. Two clear directions emerged from this process. The first was a mobile application for dyadic peer mentorship, connecting people with a specific health condition with those who have faced the same condition in the past. The key technical innovation was in creating a virtual assistant to help initiate and maintain this mentorship relationship. We have developed and validated a low-fidelity version of this application. The second direction was in helping people identify local support groups that best suit their needs. This presented a substantial technical challenge, since most support group information is fragmented across hundreds of small local grassroots sites. We addressed this challenge by creating and validating a novel method for Human-Aided Information Retrieval (HAIR) that combines information retrieval, machine learning, and crowdsourcing to aggregate support group data from these local grassroots sites.
Overall, the main intellectual merit contributions of this body of work were in addressing fundamental empirical questions in social computing and health informatics, as well as leading to the design of novel systems and methods in computing.
BROADER IMPACTS:
Results from this project were disseminated through academic publications and presentations, including five full-length papers in the top venues on social computing and human information retrieval. The results and findings were also disseminated to a lay audience through a series of blog posts (on GroupLens.org and InTheRooms.com) and a webinar course aimed at medical practitioners.
This project supported training four Ph.D. students (two of who were from groups underrepresented in Computer Science), all of whom contributed to multiple phases of this project and its dissemination. Our group also mentored five undergraduate students in research through involvement in this project (three of whom were from groups underrepresented in Computer Science). Three of these students have leveraged their research experience to apply to Ph.D. programs in Computer Science to continue their development as researchers.
Finally, we also integrated research findings and outcomes from this project into curriculum development activities, including an instructional unit on big data analysis in online health communities in a large undergraduate programming course and a design challenge for a capstone course in physical computing.
Overall, the main broader impact contributions centered on broad dissemination of outcomes to relevant communities and on building national STEM capacity and diversity through curricular integration and student training.
Last Modified: 12/09/2019
Modified by: Svetlana Yarosh
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